潜艇深水通信网络通信优化方法研究与仿真

在潜艇深水通信网络优化的研究中,复杂的水波流动对高精度信号干扰一直是实现通信优化需要解决的难点。潜艇深水通信网络中,水波的大小、流动方向、下潜深度对通信节点的影响无法进行准确预测,无法准确确定过滤阀值。传统的潜艇深水通信网络通信优化方法以水波可能产生的固定破坏性干扰阀值进行估计性过滤,无法对复杂的水波干扰过程进行细分,过滤较为粗糙,造成抗干扰性能较差,通信优化效果不好。为解决上述问题,提出利用加权约束残差修正算法的潜艇深水通信网络通信优化方法。对潜艇深水通信中复杂结构水波信号进行降频和采样处理,计算水波信号之间的关联性,提取水波信号特征,构成协方差矩阵,针对上述矩阵中的特征进行分解,对分解结果进行加权约束残差修正处理,提取准确的干扰阀值,从而实现通信优化。实验结果表明,利用改进算法进行潜艇深水通信网络通信优化,能够提高信号的抗干扰性能,通信优化效果好。     

电磁波干扰下的工程GPS定位优化与仿真

研究GPS信号的优化定位问题.GPS在大气层传播中,信号要受到不可抗拒的电离层和对流层电磁波干扰,加之大城市或山区高层建筑物及树木等对信号的影响,会导致信号的非直线传播,造成定位存在多路径效应.传统GPS抗干扰定位算法主要针对静态绝对定位,对于产生多路径效应的动态干扰,定位结果跳跃较大,稳定性差.提出了一种加权约束残差修正的工程GPS抗电磁波干扰定位算法.利用数据组合方法,对工程GPS测量信号进行采集.通过加权约束残差修正方法,并对采集的GPS信号进行残差修正处理,在电磁波干扰的情况下形成深零陷,从而提高工程GPS测量信号的抗干扰性.实验结果表明,改进算法可对工程GPS测量进行电磁波抗干扰处理,能够有效提高信号的抗干扰性能.     

航空通信网络中复杂干扰过滤技术研究

航空通信环境中存在复杂的干扰信号,对正常的通信信号造成强烈的干扰;利用传统算法进行干扰信号过滤,无法避免由于干扰信号过于复杂导致过滤不充分的缺陷;提出一种基于加权残差优化算法的航空通信网络中复杂干扰过滤方法;对原始信号进行降频处理,能够消除峰值干扰信号,提高了信号的准确性;根据加权残差修正优化算法的相关原理,对通信信号进行残差优化处理,经过处理后的通信信号在受到干扰时会形成零陷,实现了对复杂干扰信号的过滤;实验结果表明,利用该算法进行航空通信网络中复杂干扰信号过滤,能够有效提高过滤的准确性,效果令人满意.     

数字化图像动态目标搜索眼动特征增强仿真

针对已有的数字化图像目标搜索算法忽略了对提取特征的增强处理,导致传统算法存在平均查准率低、虚警率高的问题,提出数字化图像目标搜索眼动特征增强算法。通过热点图方法获取眼动特征,并利用量子遗传算法对获取的眼动特征筛选和提取,实现眼动特征增强。将增强后的眼动特征输入到支持向量机的决策函数中,实现数字化图像目标搜索。仿真结果表明,所提算法的平均查准率高、虚警率低、目标搜索概率高、搜索效率理想。     

改进的生成对抗网络图像去噪算法

由于图像噪声的存在会干扰人对图像的理解,为了有效地去除噪声并获得比较好的视觉观感,提出一种基于生成对抗网络算法,该算法通过增加生成网络的宽度来获取更多的图像特征,并加入一个全局残差对输入的噪声图像进行特征的提取与学习,避免特征的丢失.网络采用对抗损失和重建损失的加权和,在去除噪声的同时能够有效地保留图像的细节信息.实验结果表明,该算法能够有效地去除图像噪声,改善图像的视觉观感.     

改进的生成对抗网络图像去噪算法

由于图像噪声的存在会干扰人对图像的理解,为了有效地去除噪声并获得比较好的视觉观感,提出一种基于生成对抗网络算法,该算法通过增加生成网络的宽度来获取更多的图像特征,并加入一个全局残差对输入的噪声图像进行特征的提取与学习,避免特征的丢失.网络采用对抗损失和重建损失的加权和,在去除噪声的同时能够有效地保留图像的细节信息.实验结果表明,该算法能够有效地去除图像噪声,改善图像的视觉观感.     

对等P2P网络中大数据关键特征挖掘模型仿真

在网络数据管理优化问题的研究中,对等P2P为点对点网络通信.由于数据特征受到主观因素的影响较大,无法形成固定的关联特征,使得关键特征定位往往需要进行较大规模的大数据对比,传统的关联规则方法应用到此网络特征搜索过程时,建立的规则往往较为混乱甚至无规则可言,造成数据特征挖掘耗时,无效挖掘行为较多,效率较低.为此,提出利用Apriori算法的对等P2P网络中大数据关键特征挖掘方法.筛选对等p2p网络中大数据特征,选取聚类中心,并针对聚类中心进行关联性计算,删除关联性较差的特征.根据Apriori算法相关理论,对数据进行连接和剪枝处理,建立大数据关键特征挖掘模型.实验结果表明,利用改进算法进行对等p2p网络中大数据关键特征挖掘,能够提高挖掘的准确性,满足p2p网络的实际需求.     

高分辨率遥感图像中桥梁自动识别方法研究

提出一种针对高分辨率遥感图像中桥梁自动识别新算法。该算法从桥梁与河流的位置关系出发,结合遥感图像的成像特点和桥梁目标的形状特征,运用模糊处理,轮廓搜索和直线拟合识别桥梁目标。整个算法流程大致可分为三个步骤,首先在底层处理运用二维特征模糊分割水体区域;然后在中层处理中,通过水体轮廓搜索潜在桥梁点,并进行直线拟合提取初略桥梁目标;后处理中则对由于环境干扰所造成的断点进行连接,恢复出完整桥梁。试验结果表明该文算法具有识别速度快,识别准确率高及虚警率低等优点,且整个算法完全自动,不需人工干预。     

多尺度残差通道注意机制下的人脸超分辨率网络

针对当前人脸超分辨率算法中存在效率不高和重建失真等问题,提出一种基于多尺度残差通道注意机制的人脸超分辨率网络.该网络采用多尺度递进形式的结构,能够同时处理不同的上采样因子.同时,为了解决冗余和无效信息给网络造成的影响,在网络的特征重建模块中引入了通道注意力机制,并融合人脸解析信息提出一种残差通道注意块,不仅提高了网络特征利用率还加强了人脸先验的约束力度.与现有算法在Helen, CelebA和LFW数据集上进行的实验结果表明,该算法无论是主观视觉质量,还是峰值信噪比和结构相似性等客观评价指标,都明显优于现有其他算法.     

颅内异常声压干扰下脑瘫病变区域分割仿真

研究脑瘫病变医学图像边缘准确分割问题.脑瘫病变医学图像受到颅内声压的干扰,在采集过程中对病变区域特征属性形成干扰,造成病变区域特征边缘模糊化.传统算法在随机声压干扰下的脑瘫病变医学图像特征边缘模糊,无法形成有效的约束,造成病变区域分割精度下降.为提高精度,提出利用GCA演化模型的脑瘫病变区域分割方法.采集脑瘫病变区域图像,计算图像中不同像素的关联性,为克服干扰,对图像像素进行碰撞运算,实现脑瘫图像边缘增强.计算SUSAN检测算子,获取GAC演化模型,对获取的结果进行抗干扰处理,实现脑瘫病变区域分割.实验结果表明,利用改进算法进行脑瘫病变区域分割,能够避免颅内异常声压的干扰,为临床诊断提供依据.     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.